Damping torque analysis for DC bus implemented damping control

Damping torque analysis is a well-developed technique for understanding and studying power system oscillations. This paper presents the applications of damping torque analysis for DC bus implemented damping control in power transmission networks in two examples. The first example is the investigation of damping effect of shunt VSC (Voltage Source Converter) based FACTS voltage control, i.e., STATCOM (Static Synchronous Compensator) voltage control. It is shown in the paper that STATCOM voltage control mainly contributes synchronous torque and hence has little effect on the damping of power system oscillations. The second example is the damping control implemented by a Battery Energy Storage System (BESS) installed in a power system. Damping torque analysis reveals that when BESS damping control is realized by regulating exchange of active and reactive power between the BESS and power system respectively, BESS damping control exhibits different properties. It is concluded by damping torque analysis that BESS damping control implemented by regulating active power is better with less interaction with BESS voltage control and more robust to variations of power system operating conditions. In the paper, all analytical conclusions obtained are demonstrated by simulation results of example power systems.

The investigation of mechanisms in environmental catalysis using time-resolved methods

The formation of nitrogen oxides (NOx) during a combustion process is difficult to avoid because of the large exotherm and the consequent problem of avoiding local high-temperature spikes. Consequently, for many applications, such as for automotive power generation, there will be a continuing need to use catalytic after-treatment to reduce harmful emissions. The investigation of the mechanisms of the key catalytic reactions in environmental catalysis can provide an insight into the action of the catalyst, and time-resolved methods offer a powerful means to study these processes under realistic conditions. The use of Temporal Analysis of Products (TAP) and Steady State Isotopic Transient Kinetic Analysis (SSITKA) methods to investigate the reduction of NOx under various experimental conditions is described. From a detailed analysis of the SSITKA profiles, it is shown that at low temperatures the mechanism for the formation of N-2 and N2O from NO may differ from the conventional high-temperature mechanism. This is supported by density functional theory calculations, which show that the barrier to the formation of N2O from the reaction of N(ads) and NO(ads) may be too high to allow this process to occur at low temperatures. The alternative reaction of NO(ads) + NO(ads) = N2O(g) + O(ads) is shown to be much more favorable and is consistent with the SSITKA analysis. The remarkable effect of hydrogen as a reductant at low temperatures is described, and alternative interpretations of the role of hydrogen are discussed.

Determining generators' contribution to loads and line flows & losses considering loop flows

This paper presents a new method for calculating the individual generators' shares in line flows, line losses and loads. The method is described and illustrated on active power flows, but it can be applied in the same way to reactive power flows.

Short, medium and long term load forecasting model and virtual load forecaster based on radial basis neural networks

Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.

Modelling gas storage with compressed air energy storage in a system with large wind penetrations

Installed wind capacity in the European Union is expected to continue to increase due to renewable energy targets and obligations to reduce greenhouse gas emissions. Renewable energy sources such as wind power are variable sources of power. Energy storage technologies are useful to manage the issues associated with variable renewable energy sources and align non-dispatchable renewable energy generation with load demands. Energy storage technologies can play different roles in electric power systems and can be used in each of the steps of the electric power supply chain. Moreover, large scale energy storage systems can act as renewable energy integrators by smoothening the variability of large penetrations of wind power. Compress Air Energy Storage is one such technology. The aim of this paper is to examine the technical and economic feasibility of a combined gas storage and compressed air energy storage facility in the all-island Single Electricity Market of Northern Ireland and the Republic of Ireland in order to optimise power generation and wind power integration. This analysis is undertaken using the electricity market software PLEXOS ® for power systems by developing a model of a combined facility in 2020.

Regulation of arsenic mobility on basaltic glass surfaces by speciation and pH

The importance of geothermal energy as a source for electricity generation and district heating has increased over recent decades. Arsenic can be a significant constituent of the geothermal fluids pumped to the surface during power generation. Dissolved As exists in different oxidation states, mainly as As(III) and As(V), and the charge of individual species varies with pH. Basaltic glass is one of the most important rock types in many high-temperature geothermal fields. Static batch and dynamic column experiments were combined to generate and validate sorption coefficients for As(III) and As(V) in contact with basaltic glass at pH 3-10. Validation was carried out by two empirical kinetic models and a surface complexation model (SCM). The SCM provided a better fit to the experimental column data than kinetic models at high pH values. However, in certain circumstances, an adequate estimation of As transport in the column could not be attained without incorporation of kinetic reactions. The varying mobility with pH was due to the combined effects of the variable charge of the basaltic glass with the pH point of zero charge at 6.8 and the individual As species as pH shifted, respectively. The mobility of As(III) decreased with increasing pH. The opposite was true for As(V), being nearly immobile at pH 3 to being highly mobile at pH 10. Incorporation of appropriate sorption constants, based on the measured pH and Eh of geothermal fluids, into regional groundwater-flow models should allow prediction of the As(III) and As(V) transport from geothermal systems to adjacent drinking water sources and ecosystems.

Analysis of Two-Speed Wind Farm Operation From Grid-Side Measurements

This paper analyzes data captured by a phasor measurement unit at a wind farm, employing two-speed induction generators, and investigates aspects of the control system's interaction with the power system. Composite superimposed transient events are proposed as a method to improve the quality of the analysis and reduce errors caused by unknowns, such as wind speed variation. A Mathworks SimPowerSystems model validates the inertia contribution of the wind farm, which is an important parameter in power systems with high wind penetration. Transients caused by turbine speed transitions are identified and explained. The analysis also highlights areas where wind farm control should be improved if useful inertia contribution is to be provided.

Modal Extraction for Wind Turbines using Moving Window Subspace Identification

This paper proposes a method for wind turbine mode identification using the multivariable output error statespace (MOESP) identification algorithm. The paper incorporates a fast moving window QR decomposition and propagator method from array signal processing, yielding a moving window subspace identification algorithm. The algorithm assumes that the system order is known as a priori and remains constant during identification. For the purpose of extracting modal information for turbines modelled as a linear parameter varying (LPV) system, the algorithm is applicable since a nonlinear system can be approximated as a piecewise time invariant system in consecutive data windows. The algorithm is exemplified using numerical simulations which show that the moving window algorithm can track the modal information. The paper also demonstrates that the low computational burden of the algorithm, compared to conventional batch subspace identification, has significant implications for online implementation.

Wind Farm Induced Oscillations

The impact of power fluctuations arising from fixed-speed wind turbines on the magnitude and frequency of inter-area oscillations was investigated. The authors used data acquisition equipment to record the power flow on the interconnector between the Northern Ireland and Republic of Ireland systems. By monitoring the interconnector oscillation using a fast Fourier transform, it was possible to determine the magnitude and frequency of the inter-area oscillation between the Northern Ireland electricity system and that of the electricity supply board. Analysis was preformed to determine the relationship (if any) between the inter-area oscillation and the observed wind power generation at the corresponding time. Subsequently, regression analysis was introduced to model this relationship between the FFT output and the wind power generation. The effect of conventional generators on the magnitude and frequency of the inter-area oscillation was also considered.

Experimentally validated partial least squares model for dynamic line rating

This study presents a model based on partial least squares (PLS) regression for dynamic line rating (DLR). The model has been verified using data from field measurements, lab tests and outdoor experiments. Outdoor experimentation has been conducted both to verify the model predicted DLR and also to provide training data not available from field measurements, mainly heavily loaded conditions. The proposed model, unlike the direct measurement based DLR techniques, enables prediction of line rating for periods ahead of time whenever a reliable weather forecast is available. The PLS approach yields a very simple statistical model that accurately captures the physical performance of the conductor within a given environment without requiring a predetermination of parameters as required by many physical modelling techniques. Accuracy of the PLS model has been tested by predicting the conductor temperature for measurement sets other than those used for training. Being a linear model, it is straightforward to estimate the conductor ampacity for a set of predicted weather parameters. The PLS estimated ampacity has proven its accuracy through an outdoor experiment on a piece of the line conductor in real weather conditions.

Testing Tidal Turbines - Part 1: Steady Towing Tests vs Tidal Moored Tests

Tidal turbines have been tested extensively at many scales in steady state flow. Testing medium- or full-scale devices in turbulent flow has been less thoroughly examined. The differences between turbine performances in these two different states are needed for testing method verification and numerical model validation. The work in this paper documents the performance of a 1/10 scale turbine in steady state pushing tests and tidal moored tests. The overall performance of the device appears to decrease with turbulent flow, though there is increased data scatter and therefore, reduced uncertainty. At maximum power performance, as velocity increases the mechanical power and electrical power reduction from steady to unsteady flow increases. The drive train conversion efficiency also decreases. This infers that the performance for this turbine design is affected by the presence of turbulent flow.

Distributed MPC for Frequency Regulation in Multi-Terminal HVDC Grids

High Voltage Direct Current (HVDC) lines allow large quantities of power to be
transferred between two points in an electrical power system. A Multi-Terminal HVDC (MTDC) grid consists of a meshed network of HVDC lines, and this allows energy reserves to be shared between a number of AC areas in an efficient manner. Secondary Frequency Control (SFC) algorithms return the frequencies in areas connected by AC or DC lines to their original setpoints after Primary Frequency Controllers have been called following a contingency. Where multiple
TSOs are responsible for different parts of a MTDC grid it may not be possible to implement SFC from a centralised location. Thus, in this paper a simple gain based distributed Model Predictive Control strategy is proposed for Secondary Frequency Control of MTDC grids which allows TSOs to cooperatively perform SFC without the need for centralised coordination.

The reaction path of CO and Fe2O3 in a chemical-looping combustion system

The reaction mechanism of CO and Fe₂O₃ in a chemical-looping combustion (CLC) was studied based on density functional theory (DFT) at B3LYP level in this paper. The structures of all reactants, intermediate, transition structures and products of this reaction had been optimized and characterized. The reaction path was validated by means of the intrinsic reaction coordinate (IRC) approach. The result showed that the reaction was divided into two steps, the adsorbed CO molecule on Fe ₂O₃ surface formed a medium state with one broken Fe-O bond in step1, and in step2, O atom broken here oxidized a subsequent CO molecule in the fuel reactor. Thus, Fe₂O₃ molecule transport O from air to oxide CO continually in the CLC process. The activation energy and rate coefficients of the two steps were also obtained.

The optimized geometric structure of the (0001) surface of α-Fe 2O3

A tridimensional model of α-Fe₂O₃ and models of (0001) and (1102) surfaces on it were built. Then the structural optimization of the (0001) surface was presented which explored the influence of the system scale and the terminal surface configuration. Four different models including two different system scale structures (MODEL□ and MODEL□) and two different terminal structures (MODEL□ and MODEL□) were analyzed in this paper. It was concluded that the boundary effect was more important in a smaller system in the structure optimization. And the Fe-terminated was more stable than the O-terminated structure which was agreed with the experiences, this structural model can be used in further work including the monatomic adsorption/desorption and the chemical reactions on this surface.